3D Modeling and preliminary ore reserve estimation of Sheikh-Ali Copper deposit
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1 3D Modeling and preliminary ore reserve estimation of Sheikh-Ali Copper deposit Maryam Sadeghbeigi and Alireza Monazami ABSTRACT In the recent years a number of Copper exploration projects have been conducted in Iran, resulting in the discovery of world class and numerous small mine able deposits. The Sheikh-Ali Copper deposit, situated in Kerman province, is one of the small scale deposits. In this case, ore reserve modeling has been used to add value to the existing data and to increase the perceived prospectively of the finds. This paper presents the results of 3D modeling of ore body and reserve estimation of that deposit.3d modeling of ore body has been conducted on the basis of exploration studies of 3 boreholes with Gems software. The exploration of this deposit is according to a new policy of Geological Survey of Iran, i.e. continuation of exploration up to pre-feasibility study phase, which is funded by government and the obtained results are available for public. According to statistical analysis of cu grade, ore reserve estimation was done with inverse square distance technique. The total ore reserve was calculated to be tones with an average grade of %5.29 cu. Introduction Geological surveys of Sheikh Ali deposit demonstrates that ore body creation is related to creation of volcanic rocks. According to some characteristics and evidences, this ore body is Cyprus massive sulfide type. Major parts of ore body are located in chert- radolarit level. Detailed exploration activities in this part are: Preparation of topographic- geological map with 1:1000 scales in 2 km 2 area Surface explorations Geophysical survey with IP technique in order to achievement of more information about variation and expansion of ore body in depth Drilling of 16 boreholes (2675 meters) Modeling of ore body 3D modeling and ore estimation was carried out with Gemcom software. First of all, assay data of samples of boreholes were gathered in suitable structures. Data of surveying imported to Gemcom software same as points and lines. In order to preparing of 3D model of topography, other data was estimated with Laplace girding technique. All of topography points is shown same as Tree angular Irregular Network (TIN) model and 3D model of topography was prepared. 3D model of topography and 3d model of boreholes was shown in fig. 1. In order to preparing 3 d model of ore body, some section must be prepared. According to geological map and boreholes location, one plan view and one inclined section of ore body was prepared in Sheikh-Ali Copper deposit. These polygons were shown in fig. 2, fig.3. After preparation of polygons, polygons invert to polylines and poly lines combine with tielines. The solid which created with tied polyline was shown in fig 4. The volume of ore body solid is calculated with Gemcom equal to m 3. With considering to average density equal to 4.65 ton per m 3, geological reserve of ore body is estimated ton. 1722
2 Statistical analysis of Cu grade Statistical parameters of cu grade such as sample number, minimum grade, maximum grade, average grade, variance, coefficient of variation, kurtosis and skewness is presented in table 1. In order to selecting ore reserve estimation method, normal histogram and logarithmic histogram of data was presented. As you see in figures 5, 6 histogram graph of data is L- shape. Minimum grade have maximum frequency and maximum grades have minimum frequency. These graphs show that frequency distribution of data is not normal. 3D semi- variograms of cu grade was plotted in various azimuths and dip with lag distance equal to 5 m. because of all of variogarms are similar to each others then the structure of ore body is isotropic. According to statistical analysis of cu grade, inverse distance method was selected for ore reserve estimation of ore body. Block model of ore body was prepared from solid. Estimation space of block model was defined as x= , y= and z=1920 m. According to geometry of ore body and block dimensions, number of rows, column and levels of blocks was defined columns=190, rows=120 and levels= 130 Block dimensions in block model was determined 1*1*1 m. according to block dimensions, blocks which must be estimated are 190, 120 and 130m. After determining of effective parameters of ore reserve estimation, the block model was prepared (fig 8). Total number of blocks was estimated Average cu grade of blocks was reported 5.29%.but Average cu grade of samples was 5.36:%. According to density of ore equal to 4.65 ton per m 3 and volume of blocks, the ore reserve was estimated ton. Metal content of ore body was estimated ton cu. After preparing of 3D block model, variance, standard deviation and coefficient of variation were 4.36(%) 2, 2.08(%) and also kurtosis and skewness were and these indicators represent estimated blocks have less variations. Average grade of blocks were 5.35% cu but Average grade of samples were 5.36% cu. Fig 10 represents variations of estimated average grades versus cut off grades and fig. 10 represents variations of metal content versus cut off grades As you see, with increasing cut off grade from 0.5 to 1 %, the average grade increases %50 and the metal content increases %74. The average grade of blocks is 5.29% cu on the basis of cut off grade 0.5 % cu. Average grade of samples was 9.04%. In this case, Standard deviation of blocks is 2.08% cu and. Standard deviation of samples was 3.14%. References 1-Monazami, A., final report of geophysics, geology and drilling results of sheikhali ore deposit, geological survey of Iran, Gemcom software manual 3- Hasanipak, A., Sharafaldin, M.,, analysis of exploration data, Madani, H., geo statistic, Hustrulid, V., Kutcha, M., designing and planning of open pit mines,
3 Table 1- statistical parameters of cu grade number Minimum Maximum Average Variance Standard coefficient of skewness kurtosis (%) (%) (%) (%)2 deviation (%) variation Fig 1- topography model and boreholes in Sheikhali ore deposit Fig 2- plan view on the basis of surface geological map Fig 3- incline section of ore body 1724
4 Fig 4-3D model of ore body Fig 5- frequency distribution of cu grade Fig 6-logarihtmic frequency distribution of cu grade 1725
5 Fig 7-3D variogarm with lag distance 5 m, azimuth and dip 0º Fig 8- block model of ore body Fig 9- variation of average grade versus cut off grade 1726
6 Fig 9- variation of metal content versus cut off grade 1727
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